Triple
T19112074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FLP impossibility result |
E467812
|
entity |
| Predicate | failureModel |
P134465
|
FINISHED |
| Object | crash failures |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: crash failures | Statement: [FLP impossibility result, failureModel, crash failures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: failureModel Context triple: [FLP impossibility result, failureModel, crash failures]
-
A.
failureCause
Indicates that one event, condition, or factor is the reason or source that caused a particular failure to occur.
-
B.
failureEvent
Indicates that an action, process, or system has not achieved its intended outcome, resulting in a failure occurrence.
-
C.
failureBehavior
Indicates how a system, component, or process is expected to respond or act when a failure or error condition occurs.
-
D.
failedOn
Indicates that an attempted action or process did not succeed when applied to a specific target, condition, or step.
-
E.
missionFailure
Indicates that an attempted mission or operation did not achieve its intended objectives or outcome.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8dd06a26481908039e2a1bae8c597 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e394969c81909d09b2300ea0e041 |
completed | April 20, 2026, 8:28 a.m. |
| PD | Predicate disambiguation | batch_69e4b9ac41848190afd0f33b42cebe99 |
completed | April 19, 2026, 11:17 a.m. |
| PDg | Predicate description generation | batch_69e4bfe8a06081909fd5c28a33e9f218 |
completed | April 19, 2026, 11:43 a.m. |
Created at: April 10, 2026, 12:04 p.m.